Human Resources AI

[00:00:00]
>> So let's go over the first user. If you go and you turn the meeting to the in your repo to three users, I have an HR AI Markdown file. But this is what we're gonna talk about. This is our first user. This is the invisible user, the user, the user, you're never gonna see but you know they're there.

[00:00:19]
They have been in HR AI first Gatekeeper that you're going to encounter, especially as a new dev, as a dev that hasn't had their first job, they're also gonna be the most difficult, gatekeeper that you're gonna encounter because you don't have the advantage of having experience. Then it can be looked at as hardcore This was a job, let's take in contract work or volunteer work they're able to like actually track the way that the use of these systems look at it is that they're gonna be able they're gonna be your hardest adversary, right?

[00:00:56]
So AI has been increasingly integrated into HR operations, in various aspects of resource HR management. Right, few types of AI tools that we're looking at today and these days also ATS think of light workable things of that nature, right? That handles the recruitment needs, that handles the primary purpose, but it's primary purpose is to work through like all your resumes, right?

[00:01:25]
So there's like 10,000 resumes, it's reading your resumes, looking for the keywords, and you're like, if you don't... Have these keywords you're fired automatically bam thank you I don't know if you've ever had this happen where you sent a resume in and then like almost immediately you've gotten an email that says thank you but you're not what we're looking for like wow how did you read that that fast.

[00:01:46]
They didn't. ATS did, right? Which is why one of the things that you need to be doing when you're working on your resumes, things like that, make sure that you have the keywords that are in these job requirements in your resumes. Because what's going to happen is when you don't have it, it quickly scans it.

[00:02:04]
It's scanning for the years, it's scanning for those languages, for those tools. And the next thing you know, oyu're either in or you're out quickly, right? Your goal is to try to bypass that system, right? Chatbots and virtual assistants, how many of us have encountered having a chat, use a chatbot on a job site or anything like that?

[00:02:27]
No one yet I've encountered it twice so far and going behind the scenes and being able to like ask about the information of that those what they do is they use LOM's and they're judging based upon your diction, your punctuation, your lack of punctuation, the average reading human, reading skill level of an American, which is a seventh grade reading level, average reading level of a programmer, which is a eighth to 10th grade reading levels.

[00:02:56]
There they are looking at all of these little keys of like how you're speaking and how you're responding to answers. And they're looking at their judging by their LOMS, their language learning models and data, they're going by this stuff. And that's what you're getting your grade off of when it comes to what you're talking about in regards to these HR models, right?

[00:03:19]
So that's another one. Predictive analytics, these tools that use AI to analyze patterns for employee behavior and predict trends. Let's say you went to K Bootcamp, X, Y, Z, and you went to K Bootcamp A, B, C. Well, the company has been hiring bootcamp grad for about 10 years and they have the data to showcase between the two of you which one's gonna be the most successful within the first two years of being in their program, right?

[00:03:51]
They collect this data, so they know that ABC boot camp, those grads tend to be 20 to 40 percent less. Be successful and within the first two years of being at this job so what we're gonna do is that we're gonna take that time and we're gonna be there be hired they're either gonna say no to ABC grant or they're gonna scrutinize ABCs work a lot harder during the interview process versus xyz's.

[00:04:21]
Because XYZ has to predictive analytics the data to support that they may be able to handle the first two years at this job or higher chance for a higher percentage of being able to support that, right? So those is, that's how they're using these tools today, and going to have three more tools so you'll be like this is gonna be crazy.

[00:04:48]
How many of you all have done, like, hacker rank or. So I have two. Anything like that when there's like a interview, job or anything like interview tech questions where you have to fill the code challenge, they just sent it to you and you have to bring it back.

[00:05:05]
>> I know I would do them for fun.
>> You would do them for fun, like never for an interview.
>> I haven't gotten any interviews yet so
>> All right okay well well they've done now is a lot of spiritual hacker rank they've started adding AI to this so where based upon the education level that you're saying or the reposing your GitHub, they are sending.

[00:05:26]
They're sending these problems to you and they're looking at the problems and generating these questions based upon what they assume your experience level is. And if you pass them or let's say you don't do something, let's say you do on a senior engineer role or let's say, great example.

[00:05:44]
If you're talking about a cloud engineering role, but you don't set up AWS amplify as a part of your or you don't even bring it up as a part of your, this is what I would do component. They're looking at this they're flagging it automatically. And there's not even a person and part of the, the initial technical spring that's even involved is just a robot.

[00:06:07]
When you and me, I will train you and them and the final is the employee engagement tool, right? So let's say you finally get a you get a initial conversation on video, and there's a one on one we're talking well the AI is a layer between you and the engagement tool and the user.

[00:06:29]
And what's happening now is that it's reading to like how you're acting. This person seems a little unsure. This person is looking at not making a lot of eye contact things that the AI is taking notes of you the user, is you know, you're being interviewed by someone else, right?

[00:06:50]
And it's helping the employer make or the person is initially contacted and connected with you is making it helping them make decisions about you. Right? So it's little this is the world you all have inherited. Unfortunately, they're getting a lot more invasive with their tactics when it comes to hiring and this is where we're going if this is where we're at, that's fine.

[00:07:14]
That is fine like we go further down on the repo I have, how to have tips tricks and how to understand all of these right so you're in the repo right now you go towards understanding I have how to use how to understand the ATS. We talked about where you how to use those keywords when a job description and a resume and a cover letter right as very very important, we want to be able to utilize this stuff against them, right, interacting with the chatbots.

[00:07:45]
Be sure you're clear and direct whenever interacting with any HR chatbot. Any website that you're interested in, any company you're interested in that has a chatbot, you wanna be clear and direct with those chatbots, right? The chatbot doesn't understand your query? Try rephrasing. Preparing for AI based interviews practice makes perfect.

[00:08:07]
You're doing a great job. You're practicing those crazy code challenges that have absolutely nothing to do with the code, you're gonna work. [LAUGH]. It is the worst way to showcase like what people are doing, but it is there makes my head hurt a little bit, but it exists.

[00:08:26]
Were there, so you keep practicing those and practice with perfect and that way you'll be able to be relaxed and natural when those interviews so when they're going through those processes, do you like I've seen this before. So let me go ahead and run this. And engagement learning tools make the most just make the most of that experience.

[00:08:50]
When I'm talking to people just like now, I'm make sure I'm making eye contact. I am using seventh seventh to eighth grade speaking language. I am also focusing on trying to make sure that I am confident or I'm being, I'm trying to integrate myself into their team, right?

[00:09:08]
What are we doing? All right, so this is what we would do as a unit. This is the why this is why I think of things I'm speaking out the how I solve problems or how I would solve problems. I'm even speaking out how if I would have this problem, how I would ask my leadership or the senior devs right like a great example is, all right, you get stuck at it I don't know if you have none of you have had interviews yet.

[00:09:34]
Right? So you have all right you, okay, so a question that gets brought up all the time is okay you're stumped on a problem how do you approach your senior dev with this. Well, this problem that you're having. Well, what I say is well, first I am going to make sure that I have tried a, b and c and I have gone to these websites, as well as review the documentation.

[00:09:59]
Then when I approach my senior developer, I am gonna showcase them the code I've been working on. I'm going to tell them the solutions that I have attempted already and then the resources I have links to the resources that I've gone to and already researched. That way it showcases to your senior developers that you have already tried, whether it is a senior dev at work or a senior dev out in the wild on Twitter or LinkedIn.

[00:10:23]
They always respond better when you have showcased your work that you've already tried to solve this and figure it out. They love, okay, I'm just trying, I'm helping you get those last 10, those last 10 inches out of a hole like 3 meters, right? I can, I can work with that, right?

[00:10:43]
So that is the best way. To when you're answering that problem and you're speaking through how to how you're going to first do the work or try to do the work and then when asked to help showcase how you try to do the work, right, so that is how we you know, circumnavigate, we never get around.

[00:11:04]
AI but we know it's not gonna work all the time, where it's mostly most of the time I've had so far. I tried this with three of my students, three of my veterans and military spouses. They weren't full time PwC students, all three of them ended up getting jobs.

[00:11:19]
And one of them end up getting a job wasn't even as a software engineer because she wanted to be a Product Manager and it they all got jobs. They all it all worked. And like, I was like, okay. So now that we're learning this, let's make sure that everybody else around us knows this.